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Cited by 33Soil Carbon and Nitrogen DynamicsSoil Management and Crop YieldSoil erosion and sediment transport

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Temporal Variability of Soil Carbon and Nitrogen in Cotton Production on the Texas High Plains

Abstract

Soil organic carbon (SOC) is a key indicator of soil health as it is important in essential soil functions related to nutrient cycling and soil productivity. Although, it can take several decades to increase SOC in semi‐arid ecoregions, it is possible that the low organic matter background in sandy soils typical of semi‐arid soils may show greater fluctuations compared to soils from other regions. This study was conducted to evaluate the temporal C and N dynamics of cotton (Gossypium hirsutum L.) cropping systems in a semi‐arid region. The effects of no‐tillage (NT) and cover crop use on SOC, potassium permanganate oxidizable carbon (POXC), inorganic nitrogen (Nᵢₙₒᵣg), and microbial respiration were investigated in a long‐term study (∼19 yr) at Lamesa, TX, comparing conventional tillage (CT), winter fallow, to no‐tillage rye cover (R‐NT), and no‐tillage mixed species cover (M‐NT) on an Amarillo fine sandy loam. Results showed SOC and POXC were greatest during periods of active cover crop and cotton root growth. Soil organic C and POXC were significantly correlated (R² = 0.75; p < 0.0001), but poorly correlated to microbial respiration (R² = 0.41, p = 0.0001; and R² = 0.02, p = 0.8781, respectively). Conservation management practices did not impact Nᵢₙₒᵣg. Soil organic C and POXC levels were more variable than previously reported and responded to active root growth in this semi‐arid, sandy soil. Core Ideas Soil organic C and K permanganate oxidizable C were more temporally var…

Overview

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Crossref · 10.2134/agronj2019.02.0066

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Citations

Cites

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Research works printed but not linked: 4

  1. Fischer J.J., 1997, Cotton and microorganisms. ARS‐138
  2. Moebius-Clune B.N., 2016, Comprehensive assessment of soil health: The Cornell framework manual
  3. NOAA, National Centers for Environmental Information, 2018, Summary of annual normals 1981–2010– Lamesa 1 SSE, TX US USC00415013
  4. USDA‐NRCS, 2016, USDA Natural Resource Conservation Service: Official soil series, Amarillo series

Cited by

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Metadata

Authors
Burke, J. A., Lewis, K. L., Ritchie, G. L., Moore‐Kucera, J., DeLaune, P. B., & Keeling, J. W.
Affiliations
  • Texas Tech University (US)
  • Texas A&M University (US)
Corresponding author
Lewis, K.L.
Venue
Agronomy Journal
Publisher
Wiley
Published
2019-09
Volume
111
Issue
5
Pages
2218-2225
ISSN
  • 0002-1962 (ISSN-L)
  • 1435-0645
OpenAlex
W2955717351
Cited by
33
References
49
Citations by year
2026: 3 · 2025: 10 · 2024: 5 · 2023: 4 · 2022: 3 · 2021: 4 · 2020: 3 · 2019: 1
FWCI
2.19
Type
journal article
Language
en
Open access
closed
Locations
Agronomy Journal (publishedVersion)
Funders
Cotton Incorporated ((grant no. 16-400-TX))
Topics
  • Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil Carbon and Nitrogen Dynamics
  • Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil Management and Crop Yield
  • Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil erosion and sediment transport
Keywords
soil organic carbon, soil nitrogen, cotton, Gossypium hirsutum, no-tillage, cover crops, microbial respiration, inorganic nitrogen, conventional tillage, winter fallow, sandy loam soil, semi-arid soils, Texas High Plains, conservation management, temporal variation, root growth

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CoChat. (2026). Citation check: Temporal Variability of Soil Carbon and Nitrogen in Cotton Production on the Texas High Plains. https://app.cochat.ai/papers/10.2134/agronj2019.02.0066
The paper
Burke, J. A., Lewis, K. L., Ritchie, G. L., Moore‐Kucera, J., DeLaune, P. B., & Keeling, J. W. (2019). Temporal Variability of Soil Carbon and Nitrogen in Cotton Production on the Texas High Plains. Agronomy Journal. https://doi.org/10.2134/agronj2019.02.0066

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.